Generalized out-of-distribution detection and beyond in vision language model era: A survey
Detecting out-of-distribution (OOD) samples is crucial for ensuring the safety of machine
learning systems and has shaped the field of OOD detection. Meanwhile, several other …
learning systems and has shaped the field of OOD detection. Meanwhile, several other …
Anomalydiffusion: Few-shot anomaly image generation with diffusion model
Anomaly inspection plays an important role in industrial manufacture. Existing anomaly
inspection methods are limited in their performance due to insufficient anomaly data …
inspection methods are limited in their performance due to insufficient anomaly data …
A diffusion-based framework for multi-class anomaly detection
Reconstruction-based approaches have achieved remarkable outcomes in anomaly
detection. The exceptional image reconstruction capabilities of recently popular diffusion …
detection. The exceptional image reconstruction capabilities of recently popular diffusion …
Real-iad: A real-world multi-view dataset for benchmarking versatile industrial anomaly detection
Industrial anomaly detection (IAD) has garnered significant attention and experienced rapid
development. However the recent development of IAD approach has encountered certain …
development. However the recent development of IAD approach has encountered certain …
Adaclip: Adapting clip with hybrid learnable prompts for zero-shot anomaly detection
Zero-shot anomaly detection (ZSAD) targets the identification of anomalies within images
from arbitrary novel categories. This study introduces AdaCLIP for the ZSAD task, leveraging …
from arbitrary novel categories. This study introduces AdaCLIP for the ZSAD task, leveraging …
Exploring plain vit reconstruction for multi-class unsupervised anomaly detection
This work studies the recently proposed challenging and practical Multi-class Unsupervised
Anomaly Detection (MUAD) task, which only requires normal images for training while …
Anomaly Detection (MUAD) task, which only requires normal images for training while …
Weakly supervised video anomaly detection and localization with spatio-temporal prompts
Current weakly supervised video anomaly detection (WSVAD) task aims to achieve frame-
level anomalous event detection with only coarse video-level annotations available. Existing …
level anomalous event detection with only coarse video-level annotations available. Existing …
A Survey on Safe Multi-Modal Learning Systems
In the rapidly evolving landscape of artificial intelligence, multimodal learning systems
(MMLS) have gained traction for their ability to process and integrate information from …
(MMLS) have gained traction for their ability to process and integrate information from …
Large language models for anomaly and out-of-distribution detection: A survey
R Xu, K Ding - arXiv preprint arXiv:2409.01980, 2024 - arxiv.org
Detecting anomalies or out-of-distribution (OOD) samples is critical for maintaining the
reliability and trustworthiness of machine learning systems. Recently, Large Language …
reliability and trustworthiness of machine learning systems. Recently, Large Language …
Rethinking Reverse Distillation for Multi-Modal Anomaly Detection
In recent years, there has been significant progress in employing color images for anomaly
detection in industrial scenarios, but it is insufficient for identifying anomalies that are …
detection in industrial scenarios, but it is insufficient for identifying anomalies that are …